Staff Machine Learning Engineer
Customer Identity
Updated on 1/31/2024
Okta

5,001-10,000 employees

Online identity verification solutions
Company Overview
Okta stands out as a leading independent identity provider, offering a robust Identity Cloud that enables secure and efficient connection between people and technologies, a feature trusted by over 10,000 organizations including prominent names like JetBlue, Nordstrom, and Slack. The company's competitive edge lies in its extensive pre-built integrations, numbering over 7,000, with applications and infrastructure providers, simplifying and securing access for people and organizations globally. Okta's culture of fostering confidence and potential in its workforce and customers, coupled with its industry leadership and technical prowess, makes it an attractive workplace.

Company Stage

N/A

Total Funding

$1.2B

Founded

2009

Headquarters

San Francisco, California

Growth & Insights
Headcount

6 month growth

2%

1 year growth

13%

2 year growth

60%
Locations
Canada
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Kubernetes
Redshift
Python
Airflow
Data Science
SQL
Java
Docker
AWS
Pandas
Scala
Snowflake
CategoriesNew
AI & Machine Learning
Software Engineering
Requirements
  • Bachelor's degree in Computer Science, Engineering, Statistics or a related quantitative field
  • Fluency in a computing language, e.g. Python, Scala, C++, Java, etc.
  • Experience with building production systems and platforms at scale
  • Knowledge in handling large datasets using SQL and databases in a business environment
  • Excellent verbal and written communication
  • Exceptional troubleshooting and problem solving skills
  • Thrive in a fast-paced, innovative environment
Responsibilities
  • Design and implement infrastructure and platform components for training, deploying, and monitoring machine learning models in production
  • Build pipelines to ingest data from myriad sources into a centralized data lake for various use cases
  • Collaborate with production engineering teams to ensure that machine learning models integrate successfully into production environments while adhering to performance and availability SLOs
  • Participate in project planning, design, development, and code reviews
  • Communicate verbally and in writing to business customers and leadership teams with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations
  • Partnership across Engineering, Product Management, Security and Design teams to solve technical and non-technical challenges
Desired Qualifications
  • Knowledge of AWS Redshift, Snowflake or similar databases
  • Experience with data workflow platforms such as Airflow, and container technologies such as Docker and Kubernetes
  • Familiar with Python and machine learning/data science libraries such as Scikit-learn and Pandas for analyzing and modeling data
  • Familiar with multiple machine learning algorithmic methodologies, such as decision trees, logistic regression, Bayesian analysis, and others
  • Superior verbal and written communication skills with the ability to advocate technical solutions effectively to data scientists, engineering teams and business audiences
  • Ability to deal well with ambiguity, ability to self-motivate, prioritizing needs, and delivering results in a dynamic environment
  • Combination of deep technical skills and business savvy to interface with all levels and disciplines within our and our customer’s organizations